Job Description

Our client, a leading financial institution, is seeking an experience d Agricultural Valuation & Machine Learning Model SME for a 3-month contract based in Sandton. This specialist role will provide expert advisory support on agricultural valuation methodologies and assist in the review, validation, and interpretation of machine learning-driven valuation models used within an agricultural finance and credit risk environment.

The successful candidate will act as the bridge between Agriculture Banking, Credit Risk, Product, Data Science, Technology, and Project teams, ensuring valuation outputs are commercially credible, practical, and aligned to business objectives.

Key Responsibilities

• Provide specialist guidance on agricultural valuation methodologies and asset pricing principles.
• Advise on the development and refinement of machine learning valuation models.
• Identify and validate key valuation drivers, assumptions, and business rules.
• Review model outputs and provide practical business recommendations.
• Conduct research on agricultural valuation practices, market trends, and benchmark data.
• Facilitate stakeholder workshops and knowledge transfer sessions.
• Translate technical modelling concepts into clear business language.
• Prepare executive presentations, research papers, and recommendation reports.
• Support governance forums, model reviews, and decision-making processes.

Minimum Requirements

• Proven experience in agricultural valuation, agribusiness economics, agricultural finance, or a related field.
• Strong understanding of valuation methodologies and collateral valuation principles.
• Exposure to analytical, statistical, or machine learning models.
• Excellent research, analytical, and documentation skills.
• Strong communication skills with the ability to engage technical, business, and executive stakeholders.
• Experience within banking, agricultural finance, credit risk, or lending environments will be highly advantageous.

Key Deliverables

• Agricultural valuation methodology recommendations.
• Model review and validation feedback.
• Market and valuation research reports.
• Stakeholder education and knowledge transfer material.
• Executive briefing papers and presentation packs.
• Valuation framework documentation.
• Inputs into proof-of-concept (POC) recommendations and implementation planning.

Apply Now!

If you are a seasoned agricultural valuation professional with strong analytical capability and the ability to work closely with data science and credit risk teams, we would like to hear from you.